Purpose: The present study aimed to develop a classification model to predict recurrence in stage II and III colon cancer, using a previously published 128-gene signature on external and independent material. Experimental Design: Microarray gene expression data from 148 patients (37 Danish patients and 111 patients retrieved from the Gene Expression Omnibus, GSE17536) with stage II and III colon cancer were analyzed using Affymetrix Arrays (Affymetrix, Santa Clara, USA). Based on a known 128-gene signature, a classification model was created with the random forest method, using a training set consisting of stage I colon cancers (with localized disease and a good prognosis) and stage IV colon cancers (with metastasis and a poor prognosis). The classifier were built to predict stage II and III colon cancers as either stage I-like (good prognosis) or stage IV-like (poor prognosis). Results: The 3-year relapse-free survival probability (RFS) of stage III patients predicted to have a good prognosis was 79% compared to 55% of patients with a poor prognosis (P = 0.177, log-rank test). The classification model could not stratify stage II colon cancer. The complete dataset representing: (1) the 37 Danish patients (2) the 111 patients retrieved from Series GSE17536 (re-used data), is linked below as a supplementary file. Tumor samples were obtained from 37 patients with stage II and III colon cancer, who underwent colon resection at the Department of Surgery, Roskilde Hospital, Denmark and the Department of Surgery, Bispebjerg Hospital, Denmark between 2001 and 2008. Purified tumor RNA was reverse-transcribed, labelled and hybridized to Affymetrix Human Genome U133 Plus 2.0 GeneChip Array (Affymetrix, Santa Clara, USA) according to the manufacturers instructions and scanned at the RH Microarray Center, Rigshospitalet, University of Copenhagen.